How Your Brain Maps Sports

Playing different sports is rather redundant. Think about the motor skills and objects of, say, hockey versus soccer. Players on two teams try to keep control of the puck/ball and put it past the opposing keeper into the goal. Tennis, badminton and volleyball share the concept of hitting an object over a net at an opponent. Football and rugby both need to advance a ball across a goal line. There are similar objects such as a ball, a goal and the field of play and movements like jumping and running. An athlete’s brain needs to learn these shared concepts early on to be able to navigate the tactics and motor skills required for different sports. Now, neuroscientists may have discovered how our brains organize this overlapping information so we don’t need to relearn the basics of each new sport.

Think about when you started driving. While you may have been taught in one particular car, you learned the more general concepts of driving and how to identify the common objects found in dozens of vehicles. Within seconds of sitting in a different car, you can recognize the steering wheel, ignition switch, pedals, lights, not to mention the basic mechanical functions of making it move.

Neuroscience has traditionally explained this ability to recognize objects by localizing it only to the visual cortex, a specific area of the brain. Now, neuroresearcher Alex Huth of the University of California – Berkeley and his team have discovered that these different categories of objects are actually represented over a larger overlapping space in the brain in the somatosensory and frontal cortices covering almost 20% of the brain.

From the same visual system modeling lab that brought us a mind-reading computer last year, Huth used a similar technique of watching the brains of five researcher volunteers while they watched two hours of movie trailers. Using fMRI scanning, the roughly 30,000 locations, also known as voxels, in the cortex were recorded while seeing over 1,700 different categories of objects and actions from the clips.

By matching the electrical pattern in the subjects’ brains with the scenes they were watching, a “semantic space” map was created showing which areas of the brain were active when seeing certain objects or actions. As seen in the image above, categories that light up the same pattern in the brain are colored the same. For example, focus on the middle of this image and you’ll see a green section that identifies human actors, including athletes. Each small leaf on each branch represents one of the 1,700 different object or action types, which is not an exhaustive list of things in our world but a good cross section.

“Our methods open a door that will quickly lead to a more complete and detailed understanding of how the brain is organized. Already, our online brain viewer appears to provide the most detailed look ever at the visual function and organization of a single human brain,” said Huth.

Indeed, that online brain viewer is a fascinating tool. By choosing an object such as “athlete” or an action such as “kicking” on one side of the viewer, you can see the corresponding layout of brain topology that is used to visualize it.

“Using the semantic space as a visualization tool, we immediately saw that categories are represented in these incredibly intricate maps that cover much more of the brain than we expected,” Huth said.

By studying the semantic map, we can see the shared properties of athletic endeavours. The athlete cluster includes “ballplayer”, “skater” and “climber.” Interestingly, a cluster called “move self”, (including actions such as reach, jump and grab), uses a separate brain network then a more general grouping called “move” (including actions of pull, drop and reach). From a skill practice perspective, the idea of a concept neighborhood makes sense as other research has shown the transferability of movements and logic from one sport to another.

In case you were wondering, vehicles do have their own semantic group including everything from a moped to a pickup to a locomotive.